Application of non-contact hematocrit prediction technologies to overcome hematocrit effects on immunosuppressant quantification from dried blood spots.

Fully automated dried blood spot (DBS) analysis for therapeutic drug monitoring (TDM) of the immunosuppressants tacrolimus, sirolimus, everolimus and cyclosporin A suffers from a so-called hematocrit (hct) effect. This effect is related to the analysis of a partial DBS punch and extractability differences imposed by blood with different hcts. As this is intrinsic to automated DBS analysis, this poses a serious drawback for accurate immunosuppressant quantification. Knowledge of a sample's hct allows to correct the derived immunosuppressant concentrations for this effect. Unfortunately, when using the DBS approach for sampling at patients' homes, this hct will typically not be available. The aim of this study was to investigate the validity of a correction algorithm during fully automated DBS analysis of immunosuppressants, based on knowledge of the DBS' hct, obtained via two distinct non-contact hematocrit prediction strategies, using either near-infrared (NIR) or ultra-violet/visible (UV/VIS) spectroscopy. For tacrolimus, sirolimus, everolimus, and cyclosporin A, 48, 47, 58 and 48 paired venous whole blood and venous DBS patient samples were collected, respectively, and analyzed using an automated DBS-MS 500 HCT extraction unit coupled to a liquid chromatography tandem mass spectrometry system. Additionally, for all 201 samples the hct of the DBS was predicted based on NIR and UV/VIS spectroscopy. For tacrolimus and cyclosporin A, both hct prediction strategies allowed for adequate correction of the hct effect. Also for sirolimus and everolimus the results greatly improved after hct correction, although a hct bias remained for sirolimus and for everolimus a slightly significant hct effect was observed after NIR- and UV/VIS-based correction. Application of both hct prediction strategies ensured that clinical acceptance limits (i.e. ≥ 80% of the samples within 20% difference compared to whole blood) were met for all analytes. In conclusion, we demonstrated that non-contact hct prediction strategies, applied in tandem with fully automated DBS analysis, can be used to adequately correct immunosuppressant concentrations, yielding a good agreement with whole blood.

Near-infrared-based hematocrit prediction of dried blood spots: An in-depth evaluation.

BACKGROUND: Dried blood spot (DBS) microsampling has gained interest in different clinical fields, owing to its many advantages compared to conventional blood sampling. However, whilst being applied for decades for screening purposes, some challenges, such as the hematocrit (Hct) effect, hinder further widespread use of DBS for quantitative purposes in clinical practice. Amongst the approaches that were developed to cope with this issue, is the Hct prediction of DBS using near-infrared (NIR) spectroscopy. METHODS: Using left-over EDTA-anticoagulated patient samples, the accuracy and precision, stability, and robustness were assessed. Furthermore, applicability of the method on capillary DBS was evaluated via finger prick samples. RESULTS: A maximal bias, respectively CV, of 0.012 L/L and 4.5% were obtained. The method was robust towards several aspects, including storage (except for storage at 60°C), measurement location, type of filter paper and spotted volume. Furthermore, the potential to predict the Hct of capillary DBS was demonstrated. CONCLUSION: A commercially available NIR set-up was extensively and successfully validated, allowing non-contact Hct prediction of DBS with excellent accuracy and precision. This allows to correct for the Hct-based bias observed in partial-punch DBS analysis and the set-up of blood-plasma conversion factors, increasing the application potential of patient-centric sampling.

Hematocrit prediction in volumetric absorptive microsamples.

Recently, volumetric absorptive microsampling (VAMS) has been suggested as an alternative to DBS sampling. With VAMS, a fixed volume of blood (approximately 10 µL) is wicked up by the absorbent tip of a collection device, independent of the hematocrit (HT) of the blood sample. This way, VAMS effectively avoids the HT bias which occurs in partial-punch DBS analysis. Nonetheless, the HT remains an important variable in VAMS analysis, particularly if VAMS-based blood results need to be converted to serum or plasma values to allow comparison with e.g. plasma-based therapeutic intervals. Indeed, an analyte's plasma to whole blood ratio may be HT-dependent. Therefore, we developed two straightforward methods to derive the HT value from a VAMS sample based on its potassium content. One of these methods uses an aqueous extraction procedure, whereas the other one requires an organic extraction. Both methods have the potential to be seamlessly integrated with most existing VAMS analyses, allowing both target analyte quantitation and potassium analysis on a single VAMS extract.